Robotics Research Internship, Humanoid Manipulation (Spring 2027) | PhD Internship

We Love AI Jobs; Boston, Northern (MA, KY); Hybrid; USD 83,000 - 125,000; Full time

Job summary

FieldAI in Boston invites a Fall 2026 PhD internship focused on humanoid manipulation, combining perception, planning and control to advance embodied intelligence.

As a research intern, you will design and evaluate manipulation strategies, contribute to robotics foundation-model data and learning pipelines, and collaborate with researchers and hardware teams with the aim of publishing a paper.

Qualifications

• Current PhD student in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, AI/ML, or a closely related field.
• Research experience in robotic manipulation, loco-manipulation, or related robotics domains.
• Strong foundation in robot kinematics, dynamics, and control.
• Proficiency in Python and/or C++, with experience using robotics or ML tooling.
• Experience designing experiments and evaluating results on robotic systems (simulation or hardware).
• Publications in leading robotics journals/conferences (ICRA, IROS, CORL, RA-L, T-RO, etc.)

Responsibilities

• Design, implement, and evaluate manipulation and loco-manipulation strategies for humanoid robots.
• Support data collection and learning frameworks for robotics foundation models and cross-platform transfer.
• Collaborate on experiments, hardware integration, and research intended for publication.

Skills

Humanoid manipulation

Robot kinematics

Robot dynamics

Robot control

Python

C++

Imitation learning

Reinforcement learning

Education

PhD student in Robotics

Tools

ROS/ROS 2

Simulation environments

Job description

This PhD internship focuses on designing and evaluating manipulation strategies for humanoid robots, including tasks that combine perception, planning, and control. The intern will contribute to robotics foundation-model data and learning work, collaborate with researchers and hardware teams, and work toward publishing research.* Internship* On-site* Current PhD student* PhD (in progress)### Skills and expertiseHumanoid manipulationRobot kinematicsRobot dynamicsRobot controlPythonC++Imitation learningReinforcement learning### Key responsibilities* Design, implement, and evaluate manipulation and loco-manipulation strategies for humanoid robots.* Support data collection and learning frameworks for robotics foundation models and cross-platform transfer.* Collaborate on experiments, hardware integration, and research intended for publication.## How this job comparesCompared with 20 open intern research jobs on October 10, 2026.Pay: This job pays $83K to $125K a year.Similar open jobs: We Love AI Jobs lists 20 open intern research jobs at 15 companies.Remote work: This job is on site. 1 of the 20 intern research jobs (5%) are remote.AI in this role: High. AI is the core of the work: building, training or deploying AI systems. The internship directly advances embodied intelligence through humanoid manipulation research and supports data pipelines used to train robotics foundation models. It includes hands-on experimentation and evaluation of robot learning capabilities.## Full descriptionFieldAI is transforming how robots interact with the real world. Our growing R&D team is based in Boston, where we develop risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence. We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment. Our solutions are already deployed globally, and we continuously improve model performance through rapid iteration driven by real field use.We are offering a Fall 2026 internship focused on humanoid manipulation for PhD students interested in advancing embodied intelligence on humanoids. As a research intern, you will work at the intersection of robotics research and applied engineering, contributing to manipulation capabilities that directly support FieldAI’s autonomy and robot learning efforts while advancing the field of robotics through academic research with the goal of publishing a paper to a leading journal or conference.What You Will Get To DoAdvance Humanoid Manipulation Research• Design, implement, and evaluate manipulation strategies for humanoid robots across diverse tasks.• Explore loco-manipulation problems that integrate perception, planning, and control.• Work towards super-human dexterity, developing systems that outperform human teleoperation.Contribute to the Research Community• Work towards publishing a paper in a leading robotics conference/journal• Work closely with other researchers, both internal and external.• Present your work at Field at robotic conferencesContribute to Robotics Foundation Model Development• Support data collection pipelines used to train robotics foundation models.• Work with embodiment-agnostic representations to enable transfer across robot platforms.• Collaborate with researchers to integrate manipulation data into scalable learning frameworks.Collaborate Across Disciplines• Work with teleoperators and field teams to refine interfaces and improve manipulation outcomes.• Partner closely with researchers and engineers to align experiments with broader autonomy goals.• Engage with mechanical and electrical engineers on hardware integration and system bring-up.What You Have• Current PhD student in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, AI/ML, or a closely related field.• Research experience in robotic manipulation, loco-manipulation, or related robotics domains.• Strong foundation in robot kinematics, dynamics, and control.• Proficiency in Python and/or C++, with experience using robotics or ML tooling.• Experience designing experiments and evaluating results on robotic systems (simulation or hardware).• Curiosity, initiative, and a strong interest in embodied intelligence and real-world robotics.• Publications in leading robotics journals/conferences (ICRA, IROS, CORL, RA-L, T-RO, etc.)The Extras That Set You Apart• Prior experience working with humanoid robots or dexterous robotic hands.• Background in learning-based manipulation, including imitation learning or reinforcement learning.• Hands-on experience running experiments on real robot hardware.• Familiarity with ROS or ROS 2.• Publications, preprints, or open-source contributions in robotics or AI.• Interest in bridging cutting-edge research with practical, field-ready robotic systems.Why Join Field AI?FieldAI is tackling one of robotics’ hardest problems: deploying robots in unstructured, previously unknown environments. Our Field Foundational ModelsTM advance perception, planning, localization, and manipulation with an emphasis on explainability and safety, so our systems can be trusted where it matters most.